Surrogate Science

By Gerd Gigerenzer, Julian N. Marewski. 2015

121 citations recorded by the source corpus.

Subfields: Artificial Intelligence, History and Philosophy of Science, Statistics and Probability

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Sander Greenland
2. Markku V. J. Maula
3. W. Stam
4. Douglas G. Altman
5. J. Carlin
6. E. van der Laan
7. Jan Dul
8. Roelof Kuik

In History and Philosophy of Science

1. Sander Greenland
2. E. van der Laan
3. Jan Dul
4. Roelof Kuik
5. Judea Pearl
6. D. Newman-Toker
7. A. Liberman

In Statistics and Probability

1. Sander Greenland
2. Douglas G. Altman
3. Markku V. J. Maula
4. W. Stam
5. Steven N. Goodman
6. Charles Poole
7. J. Carlin
8. E. van der Laan

Citations in the corpus

• A Statistical Significance Test for Necessary Condition Analysis (2020, methodology): “Statistical testing of empirical data is a complex endeavor (Forstmeier, Wagenmakers, & Parker, 2016), and no universal method exists for statistical inference (Gigerenzer & Marewski, 2015).”
• The natural selection of bad science (2016, unknown): “…for career success in science (Nosek & Lakens, 2014; Nosek et al., 2012; Ioannidis, 2014a; Vankov et al., 2014; Fischer, Ritchie & Hanspach, 2012; Brembs, Button & Munafò, 2013; Begley, Buchan & Dirnagl, 2015; MacCoun & Perlmutter, 2015; Gigerenzer & Marewski, 2015; Sills, 2016; Sarewitz, 2016).”
• Enhancing Rigor in Quantitative Entrepreneurship Research (2019, background): “However, entrepreneurship scholars must also be aware of the potential limitations of Bayesian approaches and recognize that Bayesian statistics must also be used with great care and may not always fit the purpose of a particular study (Gigerenzer & Marewski, 2015).”
• Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations (2016, background): “…and Boen 1972; Berkson 1942; Bland and Altman 2015; Chia 1997; Cohen 1994; Evans et al. 1988; Fidler and Loftus 2009; Gardner and Altman 1986; Gelman 2013; Gelman and Loken 2014; Gelman and Stern 2006; Gigerenzer 2004; Gigerenzer and Marewski 2015; Goodman 1992, 1993, 1999, 2008; Greenland 2011,”
• For and Against Methodologies: Some Perspectives on Recent Causal and Statistical Inference Debates (2017, background): “Similarly to other writers (e.g., Gigerenzer and Marewski 2015; Krieger and Davey Smith 2016; Vandenbroucke et al. 2016; VanderWeele 2016a, b), I hold that soft sciences (like epidemiology and sociology – sciences that cannot expect to discover numerically precise and general contextual laws…”